Our overall goal is to predict an individual woman's risk of developing clinically significant post-menopausal osteoporosis, using data from longitudinal studies. Developing the prediction formula requires identifying early predictors of rate of bone loss, using an individual's past bone mass to predict the future, and using the predicted bone mass in estimating the risk of fractures. We will also compare the rates of bone loss at the appendicular and axial skeleton. In addition, we will develop and implement a quality control system for repeated bone measurements. To achieve the goals, we will develop statistical procedures that can handle repeated measurements made at irregular time points and apply them to the data collected from our ongoing longitudinal studies. These new procedures will involve empirical Bayes regression. Other techniques we will use include survival analysis piecewise regression and quality control charts. The long-term objective is to identify individuals who are at high risk of developing symptomatic osteoporosis so that they can be treated prophylactically.